code: def test_fabric_optimizer_wraps():
      """Test that the FabricOptimizer fully wraps the optimizer."""
      optimizer_cls = torch.optim.SGD
      optimizer = Mock(spec=optimizer_cls)
      fabric_optimizer = _FabricOptimizer(optimizer, Mock())
      assert fabric_optimizer.optimizer is optimizer
      assert isinstance(fabric_optimizer, optimizer_cls)
      assert isinstance(fabric_optimizer, _FabricOptimizer)
      assert type(fabric_optimizer).__name__ == "FabricSGD"
  
imports: from unittest import mock
  from unittest.mock import Mock, call
  import pytest
  import torch
  from lightning.fabric.fabric import Fabric
  from lightning.fabric.plugins import Precision
  from lightning.fabric.utilities.device_dtype_mixin import _DeviceDtypeModuleMixin
  from lightning.fabric.utilities.imports import _TORCH_GREATER_EQUAL_2_1
  from lightning.fabric.wrappers import _FabricDataLoader, _FabricModule, _FabricOptimizer, _unwrap_objects, is_wrapped
  from torch.utils.data import BatchSampler, DistributedSampler
  from torch.utils.data.dataloader import DataLoader
  from tests_fabric.helpers.runif import RunIf
label_desc: Use image node_id 11 for calling a global function with example usage: test_fabric_optimizer_wraps() without return types